Background: Physiology-based severity of illness scores are often used for risk adjustment in observational studies of intensive care unit (ICU) outcome. However, the complexity and time constraints of these scoring systems may limit their use in administrative databases. Comorbidity is a main determinant of ICU outcome, and comorbidity scores can be computed based on data from most administrative databases. However, limited data exist on the performance of comorbidity scores in predicting mortality of ICU patients. Objectives: To examine the performance of the Charlson comorbidity index (CCI) alone and in combination with other readily available administrative data and three physiology-based scores (acute physiology and chronic health evaluations [APACHE] II, simplified acute physiology score [SAPS] II, and SAPS III) in predicting short- and long-term mortality following intensive care. Methods: For all adult patients (n = 469) admitted to a tertiary university–affiliated ICU in 2007, we computed APACHE II, SAPS II, and SAPS III scores based on data from medical records. Data on CCI score age and gender, surgical/medical status, social factors, mechanical ventilation and renal replacement therapy, primary diagnosis, and complete follow-up for 1-year mortality was obtained from administrative databases. We computed goodness-of-fit statistics and c-statistics (area under ROC [receiver operating characteristic] curve) as measures of model calibration (ability to predict mortality proportions over classes of risk) and discrimination (ability to discriminate among the patients who will die or survive), respectively. Results: Goodness-of-fit statistics supported model fit for in-hospital, 30-day, and 1-year mortality of all combinations of the CCI score. Combining the CCI score with other administrative data revealed c-statistics of 0.75 (95% confidence interval [CI] 0.69–0.81) for in-hospital mortality, 0.75 (95% CI 0.70–0.80) for 30-day mortality, and 0.72 (95% CI 0.68–0.77) for 1-year mortality. There were no major differences in c-statistics between physiology-based systems and the CCI combined with other administrative data. Conclusion: The CCI combined with administrative data predict short- and long-term mortality for ICU patients as well as physiology-based scores.

With recent advances in medical care, more patients are surviving critical illness,¹ putting them at risk of subsequent morbidity.^2,3 Critically ill patients are exposed to stress, including pain, respiratory distress, and delirium, all of which may impact subsequent mental health.⁴ Several studies of psychological sequelae of intensive care suggest that patients may develop a range of psychiatric disorders, including posttraumatic stress disorder, anxiety, and depression.^3,5 However, these studies were limited by small sample size and lack of comparison groups.⁶ Other studies have assessed small subgroups of critically ill patients, such as elderly patients with severe sepsis or with acute respiratory distress syndrome.^2,7 Recent data on older US patients with sepsis suggest that information regarding health status and trajectories prior to critical illness are essential for interpreting long-term outcomes.⁸ As yet, a good understanding of the burden of psychiatric illness prior to critical illness, as well as the magnitude of increased risk of psychiatric illness following critical illness remains elusive.

Introduction: Dialysis-requiring acute kidney injury (D-AKI) is common among intensive care unit (ICU) patients. However, follow-up data on the risk of end-stage renal disease (ESRD) among these patients remain sparse. We assessed the short-term and long-term risk of ESRD after D-AKI, compared it with the risk in other ICU patients, and examined the risk within subgroups of ICU patients. Methods: We used population-based medical registries to identify all adult patients admitted to an ICU in Denmark from 2005 through 2010, who survived for 90 days after ICU admission. D-AKI was defined as needing acute dialysis at or after ICU admission. Subsequent ESRD was defined as a need for chronic dialysis for more than 90 days or a kidney transplant. We computed the cumulative ESRD risk for patients with D-AKI and for other ICU patients, taking into account death as a competing risk, and computed hazard ratios (HRs) using a Cox model adjusted for potential confounders. Results: We identified 107,937 patients who survived for 90 days after ICU admission. Of these, 3,062 (2.8%) had an episode of D-AKI following ICU admission. The subsequent risk of ESRD up to 180 days after ICU admission was 8.5% for patients with D-AKI, compared with 0.1% for other ICU patients. This corresponds to an adjusted HR of 105.6 (95% confidence interval (CI): 78.1 to 142.9). Among patients who survived 180 days after ICU admission without developing ESRD (n = 103,996), the 181-day to 5-year ESRD risk was 3.8% for patients with D-AKI, compared with 0.3% for other ICU patients, corresponding to an adjusted HR of 6.2 (95% CI: 4.7 to 8.1). During the latter period, the impact of AKI was most pronounced in the youngest patients, aged 15 to 49 years (adjusted HR = 12.8, 95% CI: 6.5 to 25.4) and among patients without preexisting chronic kidney disease (adjusted HR = 11.9, 95% CI: 8.5 to 16.8). Conclusion: D-AKI is an important risk factor for ESRD for up to five years after ICU admission.